Simultaneous Acquisition of High Quality RGB Image and Polarization Information using a Sparse Polarization Sensor

Kurita, Teppei; Kondo, Yuhi; Sun, Legong; Moriuchi, Yusuke

doi:10.1109/wacv56688.2023.00026

Cited by 3 publications

(3 citation statements)

References 61 publications

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“…Efficient demosaicing algorithms are required to prevent color and polarization reconstruction artifacts [ 125 , 144 , 145 ]. Alternate geometries combining CFA and PFA were proposed in order to maximize the signal to noise ratio or minimize the reconstruction artifacts [ 145 , 146 , 147 ].…”

Section: Embedded Polarization Imagingmentioning

confidence: 99%

Passive Polarized Vision for Autonomous Vehicles: A Review

Serres,

Lapray,

Viollet

et al. 2024

Sensors

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This review article aims to address common research questions in passive polarized vision for robotics. What kind of polarization sensing can we embed into robots? Can we find our geolocation and true north heading by detecting light scattering from the sky as animals do? How should polarization images be related to the physical properties of reflecting surfaces in the context of scene understanding? This review article is divided into three main sections to address these questions, as well as to assist roboticists in identifying future directions in passive polarized vision for robotics. After an introduction, three key interconnected areas will be covered in the following sections: embedded polarization imaging; polarized vision for robotics navigation; and polarized vision for scene understanding. We will then discuss how polarized vision, a type of vision commonly used in the animal kingdom, should be implemented in robotics; this type of vision has not yet been exploited in robotics service. Passive polarized vision could be a supplemental perceptive modality of localization techniques to complement and reinforce more conventional ones.

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Section: Embedded Polarization Imagingmentioning

confidence: 99%

Passive Polarized Vision for Autonomous Vehicles: A Review

Serres,

Lapray,

Viollet

et al. 2024

Sensors

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“…Some polarization image databases or datasets depicting polarization scenes have been reported in the literature over the last few years. [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18] They contain the capture of various scenes under natural or artificial (be it controlled or not) illumination. They present very different characteristics: some of them are partly synthetic, some of them also contain depth information, ...…”

Section: Overview Of Existing Polarization Databasesmentioning

confidence: 99%

“…Some polarization image databases or datasets depicting real world scenes have been reported over the past few years. [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18] Availability of high bandwidth communication networks and large data repositories allows researchers to easily share reference databases, especially with the development of open data. Their content is diverse, as well as the way they were captured.…”

Section: Introductionmentioning

confidence: 99%

Production of high-resolution reference polarization images from real world scenes

Bigué,

Foulonneau,

Lapray

2023

Polarization Science and Remote Sensing XI

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A few polarization image datasets depicting real world scenes have been reported. Some of them are available on an open-data basis. Some databases contain color images, often with color bands reconstructed from a sensor equipped with a Bayer filter. Unfortunately, even if these real-world images depict a variety of objects and situations and have a good overall quality (ie the spectral bands and the various polarization channels are or can be registered, noise is reduced), they often have a low definition (smaller than 1 Mp), a low bit depth and are captured with a large lens aperture, resulting in very band-limited images. Moreover, the demosaicing procedure used to reconstruct the various color bands has a smoothing effect, reducing their resolution. This latter point proves detrimental when it comes to use these images as references for demosaicing algorithms, especially for RGB images: since each channel combining polarization direction and spectral band is very sparse in the base mosaic pattern, artifacts likely to appear are considerably underestimated with band-limited images. In this work, we review existing polarization image databases, focus on non-mosaiced datasets and propose a technique to produce HD polarization images with superior quality.

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